Method and system for broadband analog to digital converter technology

ABSTRACT

Nonlinearity correction in a device that performs analog-to-digital conversion on received analog signals, may be calibrated by generating correction-parameters estimation which when applied to the total spectral content reduces distortion resulting from said nonlinearity in originally-unoccupied spectral regions. Digital signals generated based on sampling of the received analog signals may then be corrected, to remove nonlinearity related distortion, based on the estimated correction-parameters. The nonlinearity calibration may be performed during reception and handling of said analog signals. The correction-parameters may be generated based on signals located in particular spectral regions, such as the originally-unoccupied spectral regions. These signals may be injected within the device, into the particular spectral regions, and the signal may have known characteristics to enable estimating the required correction.

CLAIM OF PRIORITY

This patent application is a continuation of U.S. patent applicationSer. No. 15/012,313, filed Feb. 1, 2016, which is a continuation of U.S.patent application Ser. No. 14/746,314, filed Jun. 22, 2015, which is acontinuation of U.S. patent application Ser. No. 14/087,710, filed Nov.22, 2013, which in turn is a continuation of U.S. patent applicationSer. No. 13/345,063 filed on Jan. 6, 2012. Each of the above identifiedapplications is hereby incorporated herein by reference in its entirety.

FIELD OF THE INVENTION

Certain embodiments of the invention relate to signal processing. Morespecifically, certain embodiments of the invention relate to a methodand system for broadband signal acquisition and analog to digitalconversion technology.

BACKGROUND OF THE INVENTION

Information, including content communicated over broadband connection,is typically carried using analog signals transmitted over wirelessand/or wired connections. Therefore, extracting broadband informationrequires performing analog-to-digital conversion at the receiving end.Reception of analog signals, and analog-to-digital conversion performedthereon, however, may introduce errors and/or distortion. The errorand/or distortion may be causes by nonlinearity exhibited by receivingsystem, and/or by various components thereof that are utilized duringreception, handling and/or conversion of analog signals into theircorresponding discrete counterparts.

Further limitations and disadvantages of conventional and traditionalapproaches will become apparent to one of skill in the art, throughcomparison of such systems with some aspects of the present invention asset forth in the remainder of the present application with reference tothe drawings.

BRIEF SUMMARY OF THE INVENTION

A system and/or method is provided for broadband signal acquisition andanalog to digital conversion technology, substantially as shown inand/or described in connection with at least one of the figures, as setforth more completely in the claims.

These and other advantages, aspects and novel features of the presentinvention, as well as details of an illustrated embodiment thereof, willbe more fully understood from the following description and drawings.

BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a block diagram that illustrates an exemplary communicationnetwork that supports broadband connectivity, which may be utilized inconnection with the invention.

FIG. 2 is a block diagram that illustrates an exemplary broadbandreceiver, which may be utilized in connection with the invention.

FIG. 3A is a block diagram illustrating foreground calibration ofanalog-to-digital nonlinearity in a broadband receiver using trainingsignals, which may be utilized in connection with the invention.

FIG. 3B is a block diagram illustrating pseudo-blind foregroundcalibration of analog-to-digital nonlinearity in a broadband receiverusing training signals only in the analog domain, in accordance with anembodiment of the invention.

FIG. 4A is a block diagram illustrating background calibration ofanalog-to-digital nonlinearity in a broadband receiver using trainingsignals, in accordance with an embodiment of the invention.

FIG. 4B is a block diagram illustrating pseudo-blind backgroundcalibration of analog-to-digital nonlinearity in a broadband receiverusing training signals only in the analog domain, in accordance with anembodiment of the invention.

FIG. 4C is a block diagram illustrating background calibration ofanalog-to-digital nonlinearity in a broadband receiver using trainingsignals and with isolation filtering in the digital domain, inaccordance with an embodiment of the invention.

FIG. 4D is a block diagram illustrating pseudo-blind backgroundcalibration of analog-to-digital nonlinearity in a broadband receiver,without training signals, using isolation filtering in the digitaldomain, in accordance with an embodiment of the invention.

FIG. 5A is a diagram illustrating frequency domain representations ofsampling of a multi-band signal in which one of the bands may havevariable center frequency, in connection with an embodiment of theinvention.

FIG. 5B is a block diagram illustrating signal processing system thatsupports use of secondary subsampling during handling of multi-bandsignals to recover bands subjected to self-aliasing, in accordance withan embodiment of the invention.

FIG. 5C is a block diagram illustrating an exemplary secondarysubsampling path in an analog front-end, in accordance with anembodiment of the invention.

FIG. 6A is a flow chart that illustrates exemplary steps for performingnonlinearity correction and calibration, in accordance with anembodiment of the invention.

FIG. 6B is a flow chart that illustrates exemplary steps for performingsecondary subsampling, in accordance with an embodiment of theinvention.

DETAILED DESCRIPTION OF THE INVENTION

Certain embodiments of the invention may be found in a method and systemfor broadband analog to digital converter technology. In variousembodiments of the invention, a device that performs analog-to-digitalconversions, may be configured to correct nonlinearity associated withreception of analog signals and analog-to-digital conversion of thereceived analog signals, based on a particular nonlinearity correctionmodel. In particular, the device may be configured to calibrate thenonlinearity correction, and nonlinearity calibration may comprisegenerating and/or estimating correction parameters, which when appliedvia the particular nonlinearity correction model, to the total spectralcontent, may reduce distortion resulting from the system's nonlinearityin originally-unoccupied spectral regions. The device may then correct,using the applicable nonlinearity correction model and the estimatedcorrection parameters, digital signals generated based on the samplingof the received analog signals. The device may be configured to performthe nonlinearity correction calibration during reception and handling ofthe analog signals. The correction estimation parameters may begenerated and/or estimated based on signals in particular spectralregions. In this regard, the particular spectral regions may correspondto the originally-unoccupied spectral regions. The nonlinearitycorrection calibration may comprise injecting specific signals, such astraining signals, in the particular spectral regions. The specificsignals may have known characteristics (e.g., frequency, amplitude,phase, etc.). Accordingly, the generation and/or estimation of thecorrection estimation parameters may be based on the injected specificsignals. The nonlinearity correction calibration may comprise isolatingsignals, or content located in the particular spectral regions, whereinthe correction estimation parameters may be generated and/or estimationmay be performed based on that isolation. The isolating of signalsand/or content located in the particular spectral regions may beperformed before, during, or after correcting the digital signals.

The device may also be configured to perform secondary subsampling, toenable acquiring a particular band of a multiband signal when theparticular band is self-aliased during the sampling of another, primaryband of the multiband signal. In this regard, acquiring the particularband during the secondary subsampling may comprise generating aplurality of components corresponding to the particular band based onsampling of the particular band and sampling of the primary band, andcombining the plurality of components to reconstruct the particularband. Use of secondary subsampling may be optional, with that functionbeing disabled, for example, when sampling of the primary band isdetermined to not cause self-aliasing of the particular band. During thesecondary subsampling, a first component of the particular band may begenerated based on high-pass filtering and then decimating of an outputof analog-to-digital conversion of the output of the sampling of theprimary band. A second component may be generated by low-pass filteringand then re-sampling of the output of analog-to-digital conversion ofthe output of the sampling of the primary band; and then subtracting thelow-pass filtered and re-sampled output from an output ofanalog-to-digital conversion of the output of the sampling of theparticular band.

FIG. 1 is a block diagram that illustrates an exemplary communicationnetwork that supports broadband connectivity, in accordance with anembodiment of the invention. Referring to FIG. 1, there is shown abroadband receiver 102, local network devices 104A and 104B, broadbandnetwork 110, and a plurality of provider head-ends 120 ₁ . . . 120 _(N).

Each of the plurality of provider head-ends 120 ₁ . . . 120 _(N) maycomprise equipment comprising suitable logic, circuitry, interfaces,and/or code operable to communicate multimedia and/or Internet contentvia connections 122 ₁ . . . 122 _(N), respectively, over backhaul linksinto the broadband network 110. Multimedia and/or Internet content maycomprise voice, audio and/or visual content comprising, video, stillimages, animated images, graphics and/or textual content. The providerhead-ends 120 ₁ . . . 120 _(N) may correspond to cable, Internet, and/orsatellite broadcast head-ends. The connectivity between the providerhead-ends 120 ₁ . . . 120 _(N) and the broadband network 110 may beprovided, for example, via one or more optical, wired, and/or wirelesslinks. The broadband network 110 may comprise one or moreinterconnecting networks for providing broadband connectivity to aplurality of network devices that are connected, directly or indirectlyto broadband network 110. The broadband network 110 may comprise, forexample, a satellite network, cable network, the Internet, and/orsimilar local or wide area networks, which are capable of forwardingdata, which may comprise, but is not limited to Internet and/ormultimedia data, at broadband speeds.

The broadband receiver 102 may be installed in a location 100 to enableconnecting the location 100 to broadband network 110, providing,therefore, broadband connectivity to other devices in the location 100.The location 100 may correspond to a residence, a multi-tenant property,and/or a commercial or enterprise property. In this regard, thebroadband receiver 102 may facilitate and/or manage distribution ofmultimedia content received, for example, from provider head-ends 120 ₁. . . 120 _(N) via the broadband network 110. Accordingly, the broadbandreceiver 102 may comprise suitable logic, circuitry, interfaces, and/orcode for enabling broadband communication via the broadband network 110.The broadband receiver 102 may also comprise suitable logic, circuitry,interfaces, and/or code to enable communicating with devices within thelocation 100, for example local network devices 104A and/or 104B, whichmay be associated with the broadband receiver 102 via a local network.The broadband receiver 102 may comprise a satellite receiver, cablereceiver, a cable modem, or like devices. The broadband receiver 102 maybe configured to support Multimedia over Coax Alliance (MoCA)connectivity.

The local network devices 104A and 104B may each comprise suitablelogic, circuitry, interfaces, and/or code for enabling performingvarious functions, operations, and/or applications within the location100. The local network devices 104A and 104B may be operable, forexample, to generate, receive, process, and/or present multimediacontent and may additionally be enabled to run a web browser or otherapplications for providing Internet services to users of the localnetwork device 104A and/or 104B. In this regard, the local networkdevices 104A and 104B may be operable to communicate utilizing one ormore wired and/or wireless standards. In an exemplary aspect of theinvention, data received, handled, and/or transmitted by the localnetwork device 104A and/or 104B may be communicated to and/or from thelocation 100 via broadband connections, using the broadband receiver102. In this regard, each of the local network devices 104A and 104B maybe operable to transmit and/or receive data via cellular, WiFi, and/orFiber based links and/or connections to the broadband receiver 102.Exemplary local network devices may comprise televisions, personalcomputers (PC), laptop computers, mobile phones, and/or personalmultimedia players.

In operation, the broadband receiver 102 may provide broadbandconnectivity in location 100. The broadband receiver 102 may be operableto, for example, process received Internet packets, communicated via thebroadband network 110, which may comprise multimedia data. The broadbandreceiver 102 may store and/or forward received data to one or more ofthe local network devices 104A and 104B. After processing the receivedpackets, to extract the multimedia content for example, the broadbandreceiver 102 may store and/or forward received data to one or more ofthe local network devices 104A and 104B. For security purposes, use ofmultimedia content communicated by the provider head-ends 120 ₁ and 120_(N) may be restricted. For example, in instances where the providerhead-ends 120 ₁ and 120 _(N) correspond to cable TV providers, use ofrestriction technologies may ensure that only subscribers may access thecommunication data, and that the use is further limited to ageographical location—e.g., a residence or an office. The broadbandconnections of the broadband receiver 102 may comprise wired connections(e.g., cable) and/or wireless (e.g., satellite), comprising physicallayers (wired and/or wireless) in which analog carrier signals areutilized to carry the data communicated via these broadband connections.For example, in digital cable, satellite, and/or terrestrial TVbroadcasts, the content (multimedia data corresponding to the TVchannels) is transmitted in the form of digitally modulated signals thatare delivered to the end users over analog carrier signals—though cabledistribution networks and/or over the air.

Thus, when handling broadband connections, the broadband receiver 102may be required to receive analog signals, and to performanalog-to-digital conversion thereof to extract the digital data carriedtherein. Analog-to-digital conversion, however, may introduce errorsand/or distortion that may degrade the quality of the digital signalsobtained from such conversion, such that the extracted digital signalsmay differ from the original digital signals transmitted by the source.One such type of errors is nonlinearity related errors, which may resultfrom one or more components utilized during the analog-to-digitalconversion having nonlinearity characteristics. Accordingly, in variousembodiments of the invention, devices performing analog-to-digitalconversion, such as broadband receiver 102 in the course of handlingbroadband connections, may be configured to correct nonlinearity errorsand/or distortion.

FIG. 2 is a block diagram that illustrates an exemplary broadbandreceiver, which may be utilized in connection with the invention.Referring to FIG. 2, there is shown the broadband receiver 102 ofFIG. 1. In particular, shown in FIG. 1 are certain components of thebroadband receiver 102, namely an analog front-end 200 and a digitalcorrector 202.

The analog front-end 200 may comprise suitable logic, circuitry,interfaces, and/or code operable to handle the reception of analogsignals carrying content processed via the broadband receiver 102. Theanalog front-end 200 may comprise, for example, a gain and filteringmodule 210, a sampler 212, and an analog-to-digital converter (ADC) 216.The gain and filtering module 210 may comprise suitable logic,circuitry, interfaces, and/or code operable to perform amplification,gain and filtering processing of analog signals, based on one or moreparticular criteria. The sampler 212 may comprise suitable logic,circuitry, interfaces, and/or code operable to sample analog signals, atparticular sampling rate. In this regard, sampling may comprise reducingcontinuous analog signals to corresponding discrete signals. The sampler212 may be operable to, for example, determine and/or generate asequence of samples—that is discrete-time signals based on the receivedanalog signals. This may be achieved by reading the value of thecontinuous input analog signal at certain, periodic intervals asdetermined by the sampling rate, while using the switching module 214 toswitch off passing of the input analog signals in between the readpoints and holding the output constant when the input signal is switchedoff. The ADC 216 may comprise suitable logic, circuitry, interfaces,and/or code operable to convert analog signals into digital signals. Inthis regard, the ADC 216 may generate the digital signals based on thesamples determined and/or generated by the sampler 212. In an exemplaryaspect of the invention, the analog front-end 200 may exhibit nonlinearbehavior, which may be static and/or dynamic, during reception of analogsignals and/or handling thereof. In this regard, nonlinearity may beintroduced because of the filtering and/or gain processing of the gainand filtering module 210, sampling operation of the sampler 212 and/orthe switching module 214 thereof, and/or operation of the ADC 216.

The digital corrector 202 may comprise suitable logic, circuitry,interfaces, and/or code operable to correct errors and/or distortionintroduced during reception and handling of analog signals. In anexemplary aspect of the invention, at least some of the errors and/ordistortion corrected via the digital corrector 202 may be caused bynonlinearity in the system, specifically in the analog front-end 202. Inthis regard, the digital corrector 202 may implement and/or utilize amathematical model to estimate or correct the nonlinear errors ordistortion in the digital output generated based the received analogsignal.

In operation, the analog front-end 200 may receive and process analogsignals that carry digital content, such as during broadbandcommunication. In this regard, the analog front-end 200 may be operableto perform gain and filtering processing of a received analog signal,which may be represented by the continuous voltage function V_(in)(t),via the gain and filtering module 210; and may then sample the receivedanalog signal via the sampler 212, at particular intervals, and performanalog-to-digital conversion based thereon via the ADC 216, to generatebased on the input (received) analog signal a corresponding flow ofvoltage samples, which may represented by the voltage function V_(O)[n].The analog front-end 200 may exhibit during reception and handling ofthe input analog signal V_(in)(t), and/or sampling thereof—that is thegeneration of the corresponding sample flow V_(O)[n], a nonlinearbehavior, which may comprise static and/or dynamic nonlinearitycharacteristics. In this regard, the input-output relationship fordynamic nonlinearity exhibited by the analog front-end 200 may bedescribed, at a sampling instance, by equation (1):

$\begin{matrix}{{V_{in}\left( {nT}_{S} \right)}\text{\textasciitilde}{\sum\limits_{k}\; {\eta_{k} \times {V_{O}^{p_{k}}\left( {nT}_{S} \right)} \times \left( \frac{d^{u_{k}}{V_{O}\left( {nT}_{S} \right)}}{{dt}^{u_{k}}} \right)^{q_{k}} \times \left( \frac{d^{v_{k}}{V_{O}\left( {nT}_{S} \right)}}{{dt}^{v_{k}}} \right)^{r_{k}}}}} & (1)\end{matrix}$

where p, q, and rε[0,N], with N being the nonlinearity order; u andvε[1,M], with M being the memory order; T_(S) being the sampling period;and η_(k) being the weight of the nonlinear term k.

Accordingly, the digital corrector 202 may be configured to implement acorrection model intended to estimate or correct the nonlinear errors inthe acquired samples. For example, where the nonlinearity exhibited bythe analog front-end 200 corresponds to equation (1), the correctionmodel implemented by the digital corrector may be based on the VolterraSeries, such that the relationship between the resultant, linear digitalsignal V_(out-linear)[n] and the generated, nonlinear samples functionV_(O)[n] may be described by equation (2):

$\begin{matrix}{{{\hat{V}}_{{in}\text{-}{linear}}\left( {nT}_{S} \right)} \text{\textasciitilde} {\sum\limits_{k}\; {\mu_{k} \times {V_{O}^{\alpha_{k}}\left\lbrack {n - {a_{k}/L}} \right\rbrack} \times {V_{O}^{\beta_{k}}\left\lbrack {n - {b_{k}/L}} \right\rbrack} \times {V_{O}^{\gamma_{k}}\left\lbrack {n - {c_{k}/L}} \right\rbrack}}}} & (2)\end{matrix}$

where α, β, γ . . . ε[0,N], with N being the nonlinearity order; a, b, c. . . ε[0,M], with M being the memory order; T_(S) being the samplingperiod; and μ_(k) being the weight of the nonlinear term k.

In various embodiments of the invention, nonlinearity models associatedwith a particular system, such as the model corresponding to thenonlinearity exhibited by the analog front-end 200, may be calibrated.In this regard, calibration of the nonlinearity model may comprisedetermining or estimating nonlinearity related parameters to enableperforming nonlinearity related corrections—that is correctingnonlinearity related errors and/or distortion—based on thesenonlinearity related parameters. For example, during nonlinearitycalibration of the analog front-end 200, weights μ_(i) of the nonlinearmodel corresponding to the nonlinearity exhibited by the analogfront-end 200, may be estimated to enable performing the correctionexpressed in equation (2). In this regard, several estimation methodsmay be utilized, such as least squares or least mean squared methods.The estimation may be performed based on particular signals. In thisregard, the particular signals may comprise signals having knowncharacteristics (e.g., frequency, amplitude and phase), and thus havingpredictable corresponding samples which may enable estimatingnonlinearity related parameters (e.g. nonlinearity weights) based onanalysis of variations in the actual, resultant samples compared to thepredictable samples—i.e., the output having signal characteristics thatare different.

In some embodiments of the invention, estimating the nonlinearityrelated parameters may be performed even without necessitating use ofparticular signals, and/or without having any knowledge of particularcharacteristics of any such signals. This may be done by focusing theestimation on particular regions in the frequency domain spectrum. Inthis regard, received (analog) signals may have corresponding signalsassociated with particular frequencies in the frequency domain spectrum,with un-occupied regions therebetween. For example, with respect to theinput signal V_(in)(t), the corresponding output frequency domainspectrum may be expected to have components only in particular frequencyregions, such as frequency regions 222 and 224, with the remainingregions being originally un-occupied regions, such as frequency region226. In this regard, content of the input signal, when observed at theoutput of a nonlinear analog front-end 200, would appear at the originallocations in the frequency domain—i.e. the original locations 222 and224, with possibly modified amplitude and phase information. Thedistortion (228), however, may be found in the output spectrum both atthe locations of signals of interest as well as originally-unoccupiedfrequency regions (e.g. 226). Accordingly, the estimation of parametersutilized in a nonlinearity correction model or algorithm, implementedvia the digital corrector 202 for example, may be performed based oncomparison of the content of the distortion-only regions (e.g. 226) ofthe output spectrum to the signal-and-distortion regions of the outputspectrum. In this regard, calibration of a nonlinearity correction modelmay be performed by determining the nonlinear weights which, whenapplied to the total spectral content, may minimize the distortion inoriginally-unoccupied spectral regions.

FIG. 3A is a block diagram illustrating foreground calibration ofanalog-to-digital nonlinearity in a broadband receiver using trainingsignals, which may be utilized in connection with the invention.Referring to FIG. 3A, there is shown the analog front-end 200 and thedigital corrector 202 of FIG. 2. Also shown in FIG. 3A are trainingsignal generator 300, the correction-parameter estimator 302, andselector modules 310 and 312.

The training signal generator 300 may comprise suitable logic,circuitry, interfaces, and/or code operable to generate signals havingparticular characteristics. In this regard, signals generated by thetraining signal generator 300 may be called training signals as they maybe utilized in determining or estimating various characteristics of asystem receiving and/or handling these signals. For example, the signalsgenerated by the training signal generator 300 may be utilized astraining signals for the purpose of determining nonlinearitycharacteristics of a particular system, such as the analog front-end200, and/or for estimating nonlinearity related parameters, such asnonlinearity weights for the nonlinearity model applicable to thesystem.

The correction estimator 302 may comprise suitable logic, circuitry,interfaces, and/or code operable to generate nonlinearity correctioninformation, which may be utilized via the digital corrector 202 tocorrect and/or reduce nonlinearity related error or distortion. In thisregard, the correction-parameter estimator 302 may be operable toestimate and/or generate nonlinearity related parameters, such asnonlinearity weights for a nonlinearity model applicable to particularsystem, based on various input information. The correction estimator 302may generate the nonlinearity correction information based on, forexample, information relating to particular signals, and/orcharacteristics thereof. These particular signals may correspond to thetraining signals being generated by the training signal generator 300for example.

The selector modules 310 and 312 may comprise suitable logic, circuitry,interfaces, and/or code for routing input signals to output signals. Inthis regard, the selector module 310 may be operable to set an outputsignal to one of a plurality of input signals; whereas the selectormodule 310 may be operable to set an input signal to one of a pluralityof available output paths. For example, the selector module 310 may beutilized to set the input to the analog front-end 200 to one of theinput analog signal or an analog training signal generated by thetraining signal generator 300. The selector module 312 may be utilizedto route the output of analog front-end 200 to either the correctionestimator 302 or to the digital corrector 202.

In operation, the system shown in FIG. 3A may be calibrated fornonlinearity correction. In this regard, the nonlinearity calibrationmay be performed only when the system is not being used for receivingand handling of input analog signals. In other words, the system mayeither be performing nonlinearity calibration or signal reception butnot both (at this same time). This is described as foregroundcalibration. To perform nonlinearity calibration, the selector module310 may be configured to pass the analog training signal V_(TRAIN)generated by the training signal generator 300, and not the actual inputanalog signal V_(in)(t), into the analog front-end 200. At the sametime, the selector module 312 is configured to pass the output of theanalog front-end 200 to the correction estimator 302. Thecorrection-parameter estimator 302 also receives digital counterpart ofthe training signal V_(TRAIN) generated by the training signal generator300, which is used by the correction estimator 202 as reference forevaluating the output of the analog front-end 200. Thecorrection-parameter estimator 302 may generate nonlinearity relatedinformation that may be needed to perform nonlinearity correction inaccordance with the applicable nonlinearity correction model, such asthe one described by equation (2). In this regard, the nonlinearityrelated information may comprise, for example, weights μ_(i). Thecorrection estimator 302 may estimate the nonlinearity correctioninformation by comparing the digital training signal V_(TRAIN) receivedfrom training signal generator 300 with the digital signal generated bythe analog front-end 200 based on the analog training signal V_(TRAIN).

Once the nonlinearity calibration is completed—that is the nonlinearitycorrection information are determined and/or estimated, the system mayswitch to normal operation. In this regard, the selector module 310 maybe configured to pass the input analog signal V_(in)(t) to the analogfront-end 200, and the selector module 312 may be configured to pass theoutput of the analog front-end 200 to the digital corrector 202. Thedigital corrector may then apply necessary nonlinearity correction,based on the applicable nonlinearity correction model, to eliminate ormitigate nonlinearity related errors or distortion using the estimatednonlinearity related information during the calibration stage.

FIG. 3B is a block diagram illustrating pseudo-blind foregroundcalibration of analog-to-digital nonlinearity in a broadband receiverusing training signals only in the analog domain, in accordance with anembodiment of the invention. Referring to FIG. 3B there is shown theanalog front-end 200 and the digital corrector 202 of FIG. 2; and thetraining signal generator 300, the correction-parameter estimator 302,and selector modules 310 and 312 of FIG. 3A. Also shown in FIG. 3B istone isolator 330.

The tone isolator 330 may comprise suitable logic, circuitry,interfaces, and/or code operable to isolate particular signals. In thisregard, the isolated signals may comprise signals fitting particularcriteria, such as being located within particular regions in thefrequency spectrum. The particular regions may correspond to thelocations of known training signals.

In operation, the system shown in FIG. 3B may generally function insimilar manner as with the system of FIG. 3A. In this regard, the systemshown in FIG. 3B may also perform foreground calibration where thecalibration stage is performed separately from, and only when the systemis not operating in normal signal handling mode; with the selectormodules 310 and 312 being utilized to control the input and output ofthe analog front-end 200 in accordance of whether the system isoperating in normal mode or in calibration mode.

In the system shown in FIG. 3B, however, the calibration is performed inpseudo-blind manner, where the correction estimation is performed basedon determination of certain characteristics of particular signals, whichmay be done by use of signal isolation, thus obviating the need todirectly receive, and process digital copies of the training signalsbeing generated by the training signal generator 300. In this regard,the signal isolation may be focused on particular regions, such asregions where training signals are injected and/or regions that areoriginally un-occupied, and thus correspond to system distortion. Use ofsignal isolation may be sufficient because during nonlinearitycalibration estimating the nonlinear correction information (e.g.nonlinear weights in the nonlinear model) may be based on correctingparticular, predetermined locations in the frequency domain orspectrum—i.e., at specific frequencies, since nonlinearity does nottypically affect the frequency of the input signals, and thus theirlocations in the frequency domain. In other words, nonlinearity relatederrors and/or distortion typically comprise changes to signals'amplitude and phase, but not frequency. Therefore, the reference signalsthat are utilized for calibration need not be accurate in terms of phaseand gain if they can be separated from distortion in a spectralsense—i.e., their locations are known.

Typical training signals, such as those generated by the training signalgenerator 300, are tone(s) ideally occupying particular points in thefrequency domain. Thus, if a tone is surrounded by distortion created byother signals in the spectrum and/or by itself, the correctionestimation may be configured such that the target of a calibration ismodified from matching the corrected output to the ideal input to simplymatching the corrected output to the isolated output training tone.Accordingly, in an exemplary embodiment, the only reference informationused for performing the correction estimation would be information aboutthe frequency location of the training tone, while information aboutphase and amplitude would not be used.

Therefore, in the embodiment shown in FIG. 3B, the estimation performedby the correction estimator 302 is based on information provided by thetone isolator 330, which pertain to tones (signals) in the output of theanalog front-end 200 at particular locations in the frequency domain.The tone isolator 330 may be configured with information defining theseparticular locations. In other words, the tone isolator 330 may be setupto focus on the locations at which the training signal generator 300injects the training signals.

FIG. 4A is a block diagram illustrating background calibration ofanalog-to-digital nonlinearity in a broadband receiver using trainingsignals, in accordance with an embodiment of the invention. Referring toFIG. 4A there is shown the analog front-end 200 and the digitalcorrector 202 of FIG. 2; and the training signal generator 300 and thecorrection estimator 302 of FIG. 3A. Also shown in FIG. 4A is adder 400.

The adder 400 may comprise suitable logic, circuitry, interfaces, and/orcode operable to combine (add) a plurality of signals.

In operation, the system shown in FIG. 4A may be calibrated fornonlinearity correction, and this can be done while the system is beingused for receiving and handling of input analog signals. In other words,the system may simultaneously perform nonlinearity calibration andsignal reception and handling. This is described as backgroundcalibration. The background calibration approach may be utilized, forexample, in scenarios where the input signals have known, unoccupiedspectral regions, where the training signals being utilized forcalibrating the system may be injected. Where a system, such as theanalog front-end 200, exhibits nonlinearity (static or dynamic), thesystem's nonlinearity would similarly affect both locations (in thefrequency domain) corresponding to regions where the content in theoriginal input signal is present and originally-unoccupied frequencyregions. Thus, calibrating the nonlinearity correction model may beperformed simply based on correcting the un-occupied regions—that isdetermining nonlinearity related information required for correcting thenonlinearity causing distortion in the originally un-occupied regions,would also enable correcting nonlinearity errors and/or distortionoriginally occupied (by actual content) regions in the spectrum.

In the embodiment shown in FIG. 4A, background nonlinearity calibrationmay be performed by injecting training (reference) signals into thesystem input to calibrate the nonlinearity correction model. In thisregard, analog training signal V_(TRAIN) generated by the trainingsignal generator 300 may be combined, via adder 400, with the inputanalog signal V_(in)(t), and the combination is then inputted into theanalog front-end 200. In this regard, the training signal generator 300may generate the training signal V_(TRAIN) such that it may be locatedwithin the frequency domain in region(s) originally un-occupied by theinput signal V_(in)(t), such as region 226. The output of the analogfront-end 200 is then passed to both the correction estimator 302 andthe digital corrector 202. The correction estimator 302 may also receivedigital counterpart of the training signal V_(TRAIN) generated by thetraining signal generator 300, which is used by the correction estimator202 as reference for evaluating the output of the analog front-end 200.The correction estimator 302 may generate nonlinearity relatedinformation (e.g. weights μ_(i)) that may be needed to performnonlinearity correction in accordance with the applicable nonlinearitycorrection model.

In this regard, the correction estimator 302 may estimate thenonlinearity correction information by analyzing the frequency spectrallocations of the training signal V_(TRAIN), which correspond to theoriginally un-occupied frequency regions, based on knowledge of thetraining signal V_(TRAIN)—since it was received from training signalgenerator 300. The correction estimator 302 may determine, based on thatanalysis, the distortion caused by the system's nonlinearity in theseregions, and accordingly may estimate the correction required tomitigate the distortion. The nonlinearity related information is thenprovided to the digital corrector 202, to enable correcting nonlinearityrelated distortion in the output signal(s). The digital corrector 202may incorporate some delay when handling the output signal received fromthe analog front-end 200, to account for the processing delays requiredfor the correction estimator 302 to perform its operation. This delaymay occur during system start-up. Any variation in the analogfront-end's nonlinearity occurring during the operation of the systemcan be potentially estimated by the correction-parameter estimator withnegligible delay.

FIG. 4B is a block diagram illustrating pseudo-blind backgroundcalibration of analog-to-digital nonlinearity in a broadband receiverusing training signals only in the analog domain, in accordance with anembodiment of the invention. Referring to FIG. 4A there is shown theanalog front-end 200 and the digital corrector 202 of FIG. 2; thetraining signal generator 300 and the correction estimator 302 of FIG.3A; the tone isolator 330 of FIG. 3B; and the adder 400 of FIG. 4A.

In operation, the system shown in FIG. 4B may generally function insimilar manner as with the system of FIG. 4A. In this regard, the systemshown in FIG. 4B may also perform background calibration, withcalibration of nonlinearity correction being performed concurrent to thereception and handling of input signals. In the system shown in FIG. 4B,however, the background calibration is performed in a pseudo-blindmanner, where the correction estimation is performed based on signalisolation, thus obviating the need to directly receive, and processdigital copies of the training signals being generated by the trainingsignal generator 300. In this regard, the estimation performed by thecorrection estimator 302 is based on information provided by the toneisolator 330, which isolate signals in the output of the analogfront-end 200 at locations in the frequency domain where the trainingsignals are injected, based on prior knowledge of originally un-occupiedregions, associated with the input signal V_(in)(t), in the spectraloutput of the analog front-end 200. Therefore, the correction estimator302 may estimate the nonlinearity correction information based onanalyzing distortion in spectral locations isolated by the tone isolator330. The correction estimator 302 may then generate or estimate thenonlinearity correction information required to perform, via the digitalcorrector 202, the applicable nonlinearity correction model.

FIG. 4C is a block diagram illustrating background calibration ofanalog-to-digital nonlinearity in a broadband receiver using trainingsignals and with isolation filtering in the digital domain, inaccordance with an embodiment of the invention. Referring to FIG. 4Cthere is shown the analog front-end 200 and the digital corrector 202 ofFIG. 2; the training signal generator 300 and the correction estimator302 of FIG. 3A; and the adder 400 of FIG. 4. Also shown in FIG. 4C is anisolation filter 420.

The isolation filter 420 may comprise suitable logic, circuitry,interfaces, and/or code operable to filter signals having particularcharacteristics and/or based on particular filtering. In this regard,the isolation filter 420 may be configured to filter signals withinparticular regions in the frequency spectrum. The particular regions maycorrespond to, for example, originally-unoccupied spectral regions, suchas region 226.

In operation, the system shown in FIG. 4C may generally function in asimilar manner as the system of FIG. 4A. In this regard, the systemshown in FIG. 4C may also perform background calibration, withcalibration of nonlinearity correction being performed concurrent to thereception and handling of input signals. Furthermore, the system shownin FIG. 4C may also allow for enhancing the correction estimation basedon post-correction isolation filtering. In this regard, use of isolationfiltering after correction may enable minimizing distortion in theoriginally-unoccupied spectral regions because the signal subjected toisolation filtering may be considered stationary during calibration,thus allowing for the use of adaptive filtering or optimizationalgorithms, including simple Least Mean Squared.

FIG. 4D is a block diagram illustrating pseudo-blind backgroundcalibration of analog-to-digital nonlinearity in a broadband receiver,without training signals, using isolation filtering in the digitaldomain, in accordance with an embodiment of the invention. Referring toFIG. 4D there is shown the analog front-end 200 and the digitalcorrector 202 of FIG. 2; the correction estimator 302 of FIG. 3A; andthe isolation filter 420 of FIG. 4C.

In operation, the system shown in FIG. 4D may perform backgroundcalibration, with calibration of nonlinearity correction being performedconcurrent to the reception and handling of input signals, and withoutany injection of training signals. Rather, the correction estimationperformed by the correction estimator 330 is solely focused ondistortion in the originally un-occupied regions. In other words,because there is no training signal injection, it is presumed that thedistortion in the originally un-occupied regions is solely caused by thesystem nonlinearity, and as such the correction estimation is based onfinding the nonlinear parameters (e.g. weights) that when applied to thetotal spectral content, would minimize the distortion inoriginally-unoccupied spectral regions as much as possible, withcomplete elimination of distortion in these regions being the ultimategoal. The correction estimation in the system shown in FIG. 4C isfurther enhanced by basing the estimation on post-correction isolationfiltering with respect to the target location—that is the originallyun-occupied regions, as described with respect to FIG. 4C. Use ofpost-correction isolation filtering, via isolation filter 420, is alsopossible because since there is no injection of training signals, therewould be no additional content in the sampled/digital signal, other thanthe distortion related content. Therefore, by filtering at theoriginally un-occupied regions, the only content obtained is distortionrelated content (e.g. resulting from system nonlinearity), and theestimation processing would be based on correction necessary to removethat distortion related content.

FIG. 5A is a diagram illustrating frequency domain representations ofsampling of a multi-band signal in which one of the bands may havevariable center frequency, in connection with an embodiment of theinvention. Referring to FIG. 5A, there is shown frequency domainspectrum diagrams 500, 510, and 520, representing voltage values asfunction of frequency, and corresponding to multi-band signals—thatsignals having in the frequency domain multiple bands at differentfrequency ranges.

The multi-band signals may comprise, for example, a cable televisionsignal, which may comprise plurality of channels at differentfrequencies corresponding to TV channels. The invention, however, is notlimited to cable television signals, and may be applied similarly to anysignals have the property of having multiple different bands. Forexample, as shown in spectrum diagram 510, the multiple bands maycomprise band A (502) and band B (504). In this regard, the band A (502)may comprise several channels or signals that exist in the spectralrange [f_(o), f₁]. The band B (504) may be a fixed channel, having abandwidth of BW_(B), being centered at a frequency f_(c) in the range offrequencies [f₂, f₃]. During reception and/or processing of the originalmulti-band signal, one or more of the corresponding bands may need to beproperly received and processed. For example, in some instances, onlythe band A (502) may need to be received, such as when only the contentcarried via band A (502) frequency is desired. At other times, however,content carried via band B (504) frequency may also be desired. In thesesituations—that is when reception of both bands, and extraction ofcontent carried therein, is desired—use of dedicated anti-aliasingprocessing, in accordance with the invention, may be necessary.

With respect to the reception of band A (502), this may be achieved bysampling at a high enough rate such that the range of frequencies [f₂,f₃], aliased or otherwise, may lie completely outside the range [f₀, f₁]at the output of the sampler. In other words, band A (502) may besampled such that band B (504) would not alias on top of band A (502).This is shown in all of spectrum diagrams 500, 510 and 510, where themirror image of band A (502), represented as A′ (506), lies beyondfrequency f₃, with the mirror image of band B (504), represented as B′(508), lying within the range of frequencies [f₂, f₃], and as such thereis no aliasing of band A (502). To that end, the lowest sampling rateF_(S) that may be utilized without the band B (504) aliasing on top ofband A (502) is given by equation (3):

$\begin{matrix}\left. {{\frac{F_{S}}{2} - f_{1}} > {f_{3} + {BW}_{B} - \frac{F_{S}}{2}}}\Rightarrow{F_{S} > {f_{3} + f_{1} + {BW}_{B}}} \right. & (3)\end{matrix}$

As for band B (504), based on the location of the center frequency f_(c)of band B (504), there are three scenarios of what may happen to band B(504) when sampling to successfully receive band A (502), as shown inthe spectrum diagrams 500, 510 and 520, respectively. In this regard, asdemonstrated in spectrum diagram 500, band B (502) may be receivedcorrectly in the sampled domain. This may occur, for example, when bandB (504) is originally centered at f_(c) having a value is less than(F_(S)−BW_(B))/2. In some instances, as demonstrated by spectrum diagram510, band B (502) may be received in mirror image B′ (504), centered atF_(S)-f_(c) with no self-aliasing. This may occur, for example, whenband B (504) is originally centered at f_(c) having a value that isgreater than (F_(S)+BW_(B))/2. In some instances, however, asdemonstrated by spectrum diagram 520, self-aliasing of the band B (504)may occur during sampling—that the mirror image of band B (502), B′(508), may alias on top of the band B (502). This may occur, forexample, when band B (504) is originally centered at f_(c) where:(F_(S)−BW_(B))/2<f_(c)<(F_(S)+BW_(B)/2. Accordingly, in variousembodiments of the invention, a system receiving and processingmulti-band signals may be configured to recover and acquire bands whichmay be subject to self-aliasing when sampling for other bands, and assuch would otherwise be lost, such as B (504) in scenario 520.

FIG. 5B is a block diagram illustrating a signal processing system thatsupports use of secondary subsampling during the handling of multi-bandsignals to recover bands subjected to self-aliasing, in accordance withan embodiment of the invention. Referring to FIG. 5B, there is shown theanalog front-end 200, the gain and filtering module 210, the sampler212, and the ADC 216 of FIG. 2. Also shown in FIG. 5B is a secondarysubsampling module 550 and a signal reconstructor 552.

The secondary subsampling module 550 may comprise suitable logic,circuitry, interfaces, and/or code for performing secondary subsamplingprocessing, to enable recovering and/or reconstructing particular bandsin multi-band signals, which may otherwise be unavailable or distorteddue to self-aliasing resulting from sampling to receive other bands. Thesecondary subsampling module 550 may, for example, be operable toperform sampling and analog-to-digital conversion, which may enablerecovering band B (502) of FIG. 5A in instances where sampling toreceive band A (502) may cause self-aliasing of band B (502), asdemonstrated by spectrum diagram 520 of FIG. 5A. The signalreconstructor 552 may comprise suitable logic, circuitry, interfaces,and/or code for performing signal reconstruction processing, subsequentto the secondary subsampling processing, to enable recovering and/orreconstructing self-aliased signals. In this regard, the operationsperformed by the signal reconstructor 552 may correspond to digitaldomain based processing performed subsequent to the secondary samplingand analog-to-digital conversion performed by the secondary subsamplingmodule 550.

Self-aliasing problems may be remedied by varying the sampling rateF_(S) to avoid self-aliasing of the desired band (e.g. band B (504)).Lowering the sampling rate F_(S) may cause temporarily aliasing of bandA (502), such as when band B (504) changes location (since it hasvariable center frequency), which may cause band B (504) to alias overband A (502), at least temporarily until the system adjusts—byreadjusting the sampling rate F_(S) again. Varying the sampling clockrate may be done using rate modification circuitry, which may interfacethe ADC output with the digital domain. If the digital domain maintainsa single clock speed then the band B (504) is recovered at the newclocking rate, independently, before re-timing to the original clockspeed.

In various embodiments of the invention, recovering, reconstructingand/or acquiring bands that are subject to self-aliasing may be achievedby use of a secondary subsampling path, which may enable performinganother out-of-phase self-aliased measurement of these bands. Thesecondary subsampling path may comprise the secondary subsampling module550, which perform the sampling and analog-to-digital conversion, andthe signal reconstructor 552, which may perform the subsequent digitaldomain based signal reconstruction operations. In this regard, thesecondary subsampling module 550 may be used, running in parallel withthe primary sampler—that is sampler 212, to sample for the self-aliasedband(s), with the signal reconstructor 552 being utilized to reconstructthe self-aliased band(s) in the digital domain, subsequent to operationsof the secondary subsampling module 550, and based on, at least in part,output of the secondary subsampling module 550. During operations of thesecondary subsampling path—that is operations of the secondarysubsampling 550 and the signal reconstructor 552, which may comprisesubsampling, analog-to-digital conversion, and reconstruction basedthereon—the secondary subsampling path may run at a lower speed and withan out-of-phase sampling clock. The output of the secondary subsamplingpath may comprise a secondary measurement of the self-aliased band(s),on top of the band(s) being sampled via the (primary) sampler 212, butseverely aliased in the secondary subsampling module 550. The signalreconstructor 552 may be utilized to reconstruct the self-aliasedband(s) based on the digital outputs of the primary path and thesecondary sampling module 550. In this regard, the output of the primarypath may correspond to the digital output corresponding to the primaryband that is targeted by the (primary) sampler 212, which may beobtained after the analog-to-digital conversion via the ADC 216. Thetotal digital output corresponding to the input analog signal may,accordingly, comprise the outputs of the primary path and the secondarypath may comprise the digital output, V_(A-total)[n], corresponding tothe primary band, band A (502), and the digital output, V_(B-total)[n],corresponding to the secondary, self-aliased band, band B (504).

The sampling rate utilized in the secondary subsampling path, which maybe different from the sampling rate used by the (primary) sampler 212,may be selected such that the target bands alias on top of the bandsbeing sampled in the primary path. In this regard, the secondarysampling rate, F_(SS), may be set to F_(S)/(2n+1), such that band B(504) may alias at F_(S)/2, and recovery of band B (502) would besimplified. The lower bound on the secondary sampling rateF_(SS)=F_(S)/(2n+1) is given by equation (4):

$\begin{matrix}{{F_{SS} = \left. {\frac{F_{S}}{{2n} + 1} > {2\; {BW}_{B}}}\Rightarrow{n < {\frac{F_{S}}{4\; {BW}_{B}} - 0.5}} \right.},{n \in \aleph}} & (4)\end{matrix}$

In an embodiment of the invention, use of the secondary subsampling pathmay be selective and/or optional. For example, because self-aliasingonly occurs in certain scenarios, as demonstrated by spectrum diagram520, recovering secondary bands may not require use of the processingperformed in the secondary subsampling path. In such instances wheresecondary bands (e.g. band B (504)) may be recovered directly in sampleddomain (e.g., spectrum diagram 500) or from their mirror images (e.g.,spectrum diagram 5 10), the secondary subsampling path may be bypassed,thus saving processing, time, and/or energy. Bypassing the secondarysubsampling path may be achieved by use of control signals, which onlyactivate (enable) the secondary subsampling path when self-aliasing mayoccur.

Timing diagrams 530 and 540 show timing of the sampling operations,corresponding to primary sampling and secondary subsampling, to enableout-of-phase sampling, and digital recovery of self-aliased bands, suchas band B (504), in accordance with an embodiment of the invention. Inthis regard, timing diagram 530 shows sampling timing of primarysampling, performed via the sampler 212, of band A (502), at thecorresponding sampling rate, F_(S), which enable capturing band A (502)perfectly, and generating its corresponding digital outputV_(A-total)[n]. Accordingly, as shown in the timing diagram 540, torecover band B (504) and to generate its corresponding digital outputV_(B-total)[n], via the secondary subsampling module 550 and the signalreconstructor 552, the primary digital output, corresponding to theanalog-to-digital conversion of the primary sampler, may be filtered andre-sampled at particular timing instances indicated by the samplingrate, F_(SS), of the secondary path. The result may then be subtractedfrom the output of analog-to-digital conversion of the samplingoperation within the secondary path to remove all aliases of the band A(502). The band B (504) may then be reconstructed, from its orthogonalmeasurements, for example by high-pass filtering then decimating theoutput of the primary sampler at second set of time instances indicatedby the sampling rate, F_(SS), of the secondary path. In this regard, thetime instances for these two sets of operation, to generate twodifferent components of the target band (e.g. band B (504)) mayalternate, as shown by timing diagrams 530 and 540. FIG. 5C described asystem for implementing the subsampling path in accordance with theembodiment disclosed herein.

While the secondary subsampling path is described herein with respect tothe analog front-end 200, use of secondary subsampling is not solimited, nor is it limited to use in conjunction with nonlinearitycorrection and calibration as described in the previous figures. Rather,secondary subsampling may be utilized, separately and/or independent ofany other processing operation, in any system receiving multi-bandsignals, where sampling a particular band may subject other band(s),which are also to be handled, to self-aliasing.

FIG. 5C is a block diagram illustrating an exemplary secondarysubsampling path in an analog front-end, in accordance with anembodiment of the invention. Referring to FIG. 5C, there is shown thesecondary subsampling module 550 and the signal reconstructor 552 ofFIG. 5B. Also shown in FIG. 5C are a secondary sampler 560, a low-passfilter (LPF) 562, a re-sampler 564, a subtractor 566, a high-pass filter(HPF) 570, a decimator 572, a combiner 574, and secondaryanalog-to-digital converter (ADC) 576. In this regard, the secondarysubsampling module 550 may comprise the secondary sampler 560 and theADC 576; whereas the signal reconstructor 552 may comprise the LPF 562,the re-sampler 564, the subtractor 566, the HPF 570, the decimator 572,and the combiner 574.

The secondary sampler 560 may be similar to the sampler 212, asdescribed with respect to FIG. 2 for example. In this regard, thesecondary sampler 560 may comprise suitable logic, circuitry,interfaces, and/or code for sampling analog signals, at a particularsampling rate, to generate a sequence of samples—that is discrete-timesignals based on input analog signals. As with the sampler 212, thesecondary sampler 560 may also be configured to read the value of thecontinuous input analog signal at certain, periodic intervals, atdetermined by its own sampling rate. The passage of the input signalsmay then be switched off, in between the read points, and the outputvoltage is held constant when the input signal is switched off.

The LPF 562 may comprise suitable logic, circuitry, interfaces, and/orcode for performing low-pass filtering operations. In this regard, theLPF 562 may be operable to pass low-frequency signals while attenuatingsignals with frequencies higher than a cutoff frequency of the LPF 562.

The re-sampler 564 may comprise suitable logic, circuitry, interfaces,and/or code operable to perform signal re-sampling, which may comprisecomputing values of new samples based on other (old) samples associatedwith the input signal.

The subtractor 566 may comprise suitable logic, circuitry, interfaces,and/or code operable to subtract an input signal from another inputsignal.

The HPF 570 may comprise suitable logic, circuitry, interfaces, and/orcode for performing high-pass filtering operations. In this regard, theHPF 562 may be operable to pass high-frequency signals while attenuatingsignals with frequencies lower than a cutoff frequency of the HPF 570.

The decimator 572 may comprise suitable logic, circuitry, interfaces,and/or code operable to perform signal decimation, which may comprisereducing the number of samples in a discrete signal.

The combiner 574 may comprise suitable logic, circuitry, interfaces,and/or code operable to combine a plurality of signals. In this regard,the combiner 574 may combine the two different components associatedwith the same signals, in a manner similar to combining the I-componentand Q-component of a signal.

The ADC 576 may be similar to the ADC 216, as described with respect toFIG. 2 for example. The ADC 576, however, may be configured to operatein accordance with the sampling rate utilized in the secondarysubsampling module 550.

In operation, the secondary subsampling module 550 and the signalreconstructor 552 may be utilized to sample, recover and reconstruct aself-aliased band during reception and handling of multi-band signal,where the self-aliasing may be cause by sampling, via a primary sampler(e.g. the sampler 212), for another band in the multi-band signal. Forexample, the secondary subsampling module 550 and the signalreconstructor 552 may enable out-of-phase sampling, and digital recoveryof band B (504) when it is self-aliased. In this regard, recovering theself-aliased band may comprise reconstructing it from its orthogonalcomponents, which may be generated based on both the primary samplingand sampling via the secondary sampler, which has a distinct samplingrate (F_(SS)). To obtain the first component, represented in FIG. 5C asV_(B1), the output of analog-to-digital conversion (via the ADC 216) ofthe primary sampler (sampler 212), represented herein as primary outputV_(digital)[@F_(S)], may be high-pass filtered via the HPF 570, and thendecimating via the decimator 572. The second component, represented inFIG. 5C as V_(B2), may be obtained by low-pass filtering, via the LPF562, the primary digital output V_(digital)[@F_(S)], and thenre-sampling it via the re-sampler 564, and then subtracting the result,via subtractor 566, from the digital output of the secondary digitaloutput, represented herein as V_(digital)[@F_(SS)]. In this regard, thesecondary digital output V_(digital)[@F_(SS)] may be obtained byperforming analog-to-digital conversion, via ADC 576, on the output onthe secondary sampler 560, which may perform a dedicated samplingoperation within the secondary subsampling module 550 to remove allaliases of the band A (502). The two components (V_(B1) and V_(B2)) maythen be combined, via the combiner 574, to obtain the digital outputV_(B-total)[n] corresponding to the self-aliased band (band B (504)).

FIG. 6A is a flow chart that illustrates exemplary steps for performingnonlinearity correction and calibration, in accordance with anembodiment of the invention. Referring to FIG. 6A, there is shown a flowchart 600 comprising a plurality of exemplary steps that may beperformed to enable nonlinearity correction and calibration duringreception of analog signals, and performing of analog-to-digitalconversion thereto, such as during broadband communications.

In step 602, an analog signal may be received and processed, such as viathe analog front-end 200. In this regard, reception and handling ofanalog signals may comprise performing such operations as amplification,gain, and/or filtering operations, sampling, and then analog-to-digitalconversion. In step 604, a determination whether the receiving systemexhibits nonlinearity may be performed. In instances where the receivingsystem does not exhibit nonlinearity, the process may conclude. Ininstances where it is determined that the receiving system does exhibitnonlinearity, the process may proceed to step 606.

In step 606, applicable nonlinearity correction models, for use incorrecting errors and distortion resulting from system's nonlinearity,may be determined. The nonlinearity correction model may be representedby equation (2) for example. In step 608, nonlinearity relatedparameters, which may be necessary for calibrating the applicablenonlinearity model, may be determined. The nonlinearity relatedparameters may comprise applicable nonlinearity weights in instanceswhere the nonlinearity correction model is similar to the modelaccording to equation (2). The nonlinearity related parameters may bedetermined and/or estimated based on particular signals. In this regard,the signals that are utilized in estimating the nonlinearity parametersmay comprise injected signals having known characteristics and/orsignals present in originally un-occupied regions. In step 610,nonlinearity correction may be applied based on the determinedapplicable nonlinearity correction model and estimated nonlinearitycorrection parameters (e.g. nonlinearity weights).

FIG. 6B is a flow chart that illustrates exemplary steps for performingsecondary subsampling, in accordance with an embodiment of theinvention. Referring to FIG. 6B, there is shown a flow chart 650comprising a plurality of exemplary steps that may be performed toenable performing secondary subsampling of multi-band signals, such asduring broadband communications.

In step 652, a determination of whether a received signal is amulti-band signal may be performed. In instances where the receivedsignal is not a multi-band signal, the process may conclude. Ininstances where the received signal is determined to be a multi-bandsignal, the process may proceed to step 654. In step 654, adetermination of whether sampling a particular band in the multi-bandsignal may cause another band to self-alias may be performed. Ininstances where no self-aliasing occurs, the process may conclude. Ininstances where it is determined that self-aliasing would occur, theprocess may proceed to step 656. In step 656, the input signal issampled via secondary sampler, having a particular sampling rate tosample for the would-be self-aliased band, and the sampling output isthen subjected to analog-to-digital conversion, to obtain the secondarydigital output. In step 658, the primary digital output, correspondingto the analog-to-digital conversion of the output of the primary samplerutilized to sample the first band, may be low-pass filtered, and thenre-sample; and the result may then be subtracted from the secondarydigital output, to generate first component of self-aliased band. Instep 660, primary digital output may be high-pass filtered, and thendecimated, to generate first component of self-aliased band. In step662, the first and second components may be combined to reconstruct theoriginal (self-aliased) band.

Various embodiments of the invention may comprise a method and systemfor broadband analog to digital converter technology. The broadbandreceiver 102 may be configured to correct, via the digital corrector202, nonlinearity associated with reception and/or handling of analogsignals, such as nonlinearity associated with the analog front-end 200during reception, handling, sampling, and/or analog-to-digitalconversion of the received analog signals thereby. In this regard, thenonlinearity correction may be performed in accordance with a particularnonlinearity correction model, such as the model described by equation(2). The broadband receiver 102 may be configured to calibrate thenonlinearity correction, where the nonlinearity calibration may comprisegenerating and/or estimating, via the correction estimator 302 forexample, correction estimation parameters, such as weights μ_(i), whichwhen applied via the particular nonlinearity correction model, to totalspectral content may reduce distortion resulting from the system'snonlinearity in originally-unoccupied spectral regions. The broadbandreceiver 102 may then correct, via the digital corrector 202, using theapplicable nonlinearity correction model and the estimated correctionestimation parameters, digital signals generated, by the analogfront-end 200, based on sampling and/or conversion of the receivedanalog signals. The broadband receiver 102 may be configured to performthe nonlinearity correction calibration during reception and handling ofthe analog signals.

The correction estimation parameters may be generated and/or estimatedbased on signals in particular spectral regions. In this regard, theparticular spectral regions may correspond to the originally-unoccupiedspectral regions (e.g. region 226). The nonlinearity correctioncalibration may comprise injecting specific signals, such as trainingsignals generated by the training signal generator 300, in theparticular spectral regions. The specific signals may have knowncharacteristics (e.g., frequency, amplitude, phase, etc.). Accordingly,the generation and/or estimation of the correction estimationparameters, by the correction estimator 302, may be based on theinjected specific signals. The nonlinearity correction calibration maycomprise isolating, via the tone isolator 330 and/or the isolationfilter 420, signals or content located in the particular spectralregions, wherein the correction estimation parameters may be generatedand/or estimation may be performed based on that isolation. Theisolating of signals and/or content located in the particular spectralregions may be performed before or after correcting the digital signals.

The broadband receiver 102 may also be configured to perform secondarysubsampling, via a secondary subsampling path comprising the secondarysubsampling module 550 and the signal reconstructor 552 for example, toenable acquiring a particular band, such as band B (504) of a multibandsignal when the particular band is self-aliased during sampling ofanother, primary band of the multiband signal, such as band A (502). Inthis regard, acquiring and/or reconstructing the particular band duringthe secondary subsampling may comprise generating a plurality ofcomponents corresponding to the particular band, which may be generatedbased on analog-to-digital conversion of outputs of sampling of theparticular band and sampling of the primary band, using the sampler 212,the ADC 216, and the secondary subsampling module 552; and combining theplurality of components to reconstruct the particular band, via thecombiner 574 for example. Use of secondary subsampling may be optional,with that function being disabled, for example, when sampling of theprimary band is determined to not cause self-aliasing of the particularband. During the secondary subsampling, a first component of theparticular band may be generated based on high-pass filtering, via theHPF 570, and then decimating, via the decimator 572, of an output ofanalog-to-digital conversion of the output of the sampling of theprimary band, corresponding to the output of ADC 216. A second componentmay be generated by low-pass filtering, via the LPF 562, and thenre-sampling, via the re-sampler 564, of the output of analog-to-digitalconversion of the output of the sampling of the primary band; and thensubtracting, via the subtractor 566, the low-pass filtered andre-sampled output from an output of analog-to-digital conversion of theoutput of sampling of the particular band, corresponding to the outputof ADC 576 of the secondary subsampling module 552 for example.

Other embodiments of the invention may provide a non-transitory computerreadable medium and/or storage medium, and/or a non-transitory machinereadable medium and/or storage medium, having stored thereon, a machinecode and/or a computer program having at least one code sectionexecutable by a machine and/or a computer, thereby causing the machineand/or computer to perform the steps as described herein for broadbandanalog to digital converter technology.

Accordingly, the present invention may be realized in hardware,software, or a combination of hardware and software. The presentinvention may be realized in a centralized fashion in at least onecomputer system, or in a distributed fashion where different elementsare spread across several interconnected computer systems. Any kind ofcomputer system or other apparatus adapted for carrying out the methodsdescribed herein is suited. A typical combination of hardware andsoftware may be a general-purpose computer system with a computerprogram that, when being loaded and executed, controls the computersystem such that it carries out the methods described herein.

The present invention may also be embedded in a computer programproduct, which comprises all the features enabling the implementation ofthe methods described herein, and which when loaded in a computer systemis able to carry out these methods. Computer program in the presentcontext means any expression, in any language, code or notation, of aset of instructions intended to cause a system having an informationprocessing capability to perform a particular function either directlyor after either or both of the following: a) conversion to anotherlanguage, code or notation; b) reproduction in a different materialform.

While the present invention has been described with reference to certainembodiments, it will be understood by those skilled in the art thatvarious changes may be made and equivalents may be substituted withoutdeparting from the scope of the present invention. In addition, manymodifications may be made to adapt a particular situation or material tothe teachings of the present invention without departing from its scope.Therefore, it is intended that the present invention not be limited tothe particular embodiment disclosed, but that the present invention willinclude all embodiments falling within the scope of the appended claims.

What is claimed is:
 1. A method, comprising: in a device that performsanalog-to-digital conversion, calibrating nonlinearity associated withanalog-to-digital conversion of received analog signals, saidcalibrating comprises generating correction estimation parameters,wherein applying said correction estimation parameters to total spectralcontent reduces distortion in originally-unoccupied spectral regions,said distortion resulting from said nonlinearity; and correcting basedon said correction estimation parameters, digital signals generatedbased on sampling of said received analog signals.
 2. The methodaccording to claim 1, comprising performing said calibration duringreception and handling of said analog signals.
 3. The method accordingto claim 1, comprising generating said correction estimation parametersbased on signals in particular spectral regions.
 4. The method accordingto claim 3, wherein said particular spectral regions correspond to saidoriginally-unoccupied spectral regions.
 5. The method according to claim3, comprising injecting specific signals in said particular spectralregions.
 6. The method according to claim 5, comprising generating saidcorrection estimation parameters based on said injected specificsignals.
 7. The method according to claim 3, comprising isolatingsignals located in said particular spectral regions, wherein saidcorrection estimation parameters are generated based on said isolatedsignals.
 8. The method according to claim 7, comprising isolating saidsignals located in said particular spectral regions after saidcorrecting of said digital signals.
 9. A system, comprising: one or morecircuits for use in a device that performs analog-to-digital conversion,said one or more circuits being operable to calibrate nonlinearityassociated with analog-to-digital conversion of received analog signals,said calibrating comprises generating correction estimation parameters,wherein applying said correction estimation parameters to total spectralcontent reduces distortion in originally-unoccupied spectral regions,said distortion resulting from said nonlinearity; and said one or morecircuits being operable to correct based on said correction estimationparameters, digital signals generated based on sampling of said receivedanalog signals.
 10. The system according to claim 9, wherein said ormore circuits are operable to perform said calibration during receptionand handling of said analog signals.
 11. The system according to claim9, wherein said or more circuits are operable to generate saidcorrection estimation parameters based on signals in particular spectralregions.
 12. The system according to claim 11, wherein said particularspectral regions correspond to said originally-unoccupied spectralregions.
 13. The system according to claim 11, wherein said or morecircuits are operable to inject specific signals in said particularspectral regions.
 14. The system according to claim 13, wherein said ormore circuits are operable to generate said correction estimationparameters based on said injected specific signals.
 15. The systemaccording to claim 11, wherein said or more circuits are operable toisolate signals located in said particular spectral regions, and saidcorrection estimation parameters are generated based on said isolatedsignals.
 16. The system according to claim 15, wherein said one or morecircuits are operable to isolate said signals located in said particularspectral regions after said correcting of said digital signals.
 17. Asystem, comprising: one or more circuits for use in a samplingcomponent, said one or more circuits being operable to acquire aparticular band of a multiband signal when said particular band isself-aliased during sampling of another band of said multiband signal,wherein said acquisition comprises: generating a plurality of componentscorresponding to said particular band based on sampling of saidparticular band and sampling of said another band; and combining saidplurality of components to reconstruct said particular band.
 18. Thesystem according to claim 17, wherein said one or more circuits areoperable to disable operation of said sampling component when samplingof said another band does not cause self-aliasing of said particularband.
 19. The system according to claim 17, wherein said one or morecircuits are operable to generate a first of said plurality ofcomponents based on high-pass filtering and then decimating of an outputof analog-to-digital conversion of said sampling of said another band.20. The system according to claim 17, wherein said one or more circuitsare operable to generate a second of said plurality of components by:low-pass filtering and then re-sampling of an output ofanalog-to-digital conversion of said sampling of said another band; andsubtracting said low-pass filtered and re-sampled output from an outputof analog-to-digital conversion of said sampling of said particularband.